Background The increased adoption of the internet, social media, wearable devices, e-
health services, and other technology-driven services in medicine and healthcare has led to …

Cardiovascular-kidney-metabolic (CKM) syndrome is a novel construct recently defined by
the American Heart Association in response to the high prevalence of metabolic and kidney …

Medical datasets are usually imbalanced, where negative cases severely outnumber
positive cases. Therefore, it is essential to deal with this data skew problem when training …

This review paper explores the transformative role of data-driven decision-making in
healthcare, focusing on how predictive modeling enhances patient outcomes. Predictive …

Background Advances in machine learning (ML) provide great opportunities in the
prediction of hospital readmission. This review synthesizes the literature on ML methods and …

Objective Despite recent calls for home healthcare (HHC) to integrate informatics, the
application of machine learning in HHC is relatively unknown. Thus, this study aimed to …

Objective Health care providers increasingly rely upon predictive algorithms when making
important treatment decisions, however, evidence indicates that these tools can lead to …

Electronic medical records are increasingly used to store patient information in hospitals and
other clinical settings. There has been a corresponding proliferation of clinical natural …

Background: Hospital readmissions are one of the costliest challenges facing healthcare
systems, but conventional models fail to predict readmissions well. Many existing models …